Enterprise Data Architect

Blackboard   •  

Washington, DC

Industry: Financial Services


11 - 15 years

Posted 422 days ago

This job is no longer available.

Enterprise Data Architect

With nearly 20,000 organizational customers and millions of student users, Blackboard is the world's leading educationtechnology and services company. Blackboard is shaping the future of education with big ideas that challenge conventional thinking and advance new models of learning. Every day we’re inspiring people to find new ways to learn, connect and drive change in the way education is delivered and experienced. Through technology and services, we bring people closer to the knowledge they seek and to ways they can change their own education and the world for the better.
The Enterprise Data Architect will report to the Blackboard CIO and will work closely with executive leadership to define the Blackboard Enterprise Data Strategy.
The ideal candidate is someone who is a hands-on analyst, technologist and architect who has deep experience in enterprise information/data management, data warehousing and analytics technologies. The Enterprise Data Architect will provide Blackboard with strategic leadership and tactical direction in the areas of (1) enterprise-wide definitional structures, (2) implementation of such structures across platforms, products, and geographic areas, and (3) business intelligence analytics, data mining, visualization and assessment of data quality. 
The Enterprise Data Architect will develop a detailed knowledge of the underlying business processes, available data, and data products. He/she will become the subject matter expert on content, current and potential future uses of enterprise data, and the quality and interrelationship between core elements of the data repository and data products.
The Enterprise Data Architect will consult with the Blackboard CEO Leadership Team, IT, data analytics, product management and development staff to design and implement scripts, programs, databases, software components and analyses that will support product quality and an in-depth understanding of potential uses of the data. Adept ability to build teams and manage cross-functional stakeholder groups is critical.
The Enterprise Data Architect has responsibility for determining the information the enterprise will capture, retain and use. This individual will possess a combination of business knowledge, technical skills, and people skills to define and guide data strategy for the global enterprise. 

Other areas of focus will include:

  • Performing a key management and thought leadership role in the areas of advanced data techniques, including data modeling, data access, data integration, data visualization, text mining, data discovery, statistical methods, database design and implementation.
  • Defining and achieving the strategy roadmap for the enterprise; including data modeling, implementation and data management for our enterprise data warehouse and advanced data analytics systems.
  • Setting the vision, gathering requirements, gaining business consensus, performing vendor and product evaluations, mentoring business and development resources, deliver solutions, training and documentation.
  • Establishing standards and guidelines for the design & development, tuning, deployment and maintenance of information, advanced data analytics, and text mining models and physical data persistence technologies.
  • Providing leadership in establishing analytic environments required for structured, semi-structured and unstructured data.
  • Translating broader business initiatives into clear team objectives and concrete individual goals, aligning appropriately with other groups for efficient, coordinated action.
  • Drawing conclusions and effectively communicates findings with both technical and non-technical team members, providing active leadership skills across project team and business community.
  • Working with leadership to understand the business requirements and business processes, design data warehouse (“DW”) schema and define extract-translate-load (“ETL”) and/or extract-load-translate (“ELT”) processes for DW.
  • Creating discover-access-distill (“DAD”) strategies to bring significant value data understanding.
  • Framing and conducting complex analyses and experiments using various statistical techniques.
  • Participating in Business Intelligence projects.



  • Minimum of Bachelor’s Degree (Computer Science, Mathematics, Statistics, IndustrialEngineering).
  • A minimum of 10 years of progressively responsibleexperience in a directly related area, during which both professional and management capabilities have been clearly demonstrated.
  • Extensive expertise in Oracle/MySQL database, SalesForce, as well as data modeling, both logical and physical.
  • Extensive experience in multidimensional data modeling
  • Extremely strong analytical and problem-solving skills.
  • Outstanding verbal, written and visual presentation skills.
  • Proven strong negotiating and consensus building abilities.
  • Proven skills to work effectively across internal functional areas in ambiguous situations.
  • Structured thinker and effective communicator, comfortable with interacting with cross functional teams.
  • Ability to work independently, establishing strategic objectives, project plans and milestone goals.
  • Extensive experience providing practical direction on information and analytics platforms in conjunction with EDW tools and technologies.
  • Experience using with project management, ITIL and SDLC methodologies.
  • Solid experience with Data Warehouse and BI systems; extensive experience for collecting business requirements from customers, and transform the requirements into DB data processes and data schema.
  • Knowledge of relational SQL databases and SQL in at least one of the following environments: Oracle. Microsoft SQL Server or MySQL.
  • Experience in and understanding of a wide variety of analytical processes (governance, measurement, information security, etc.).
  • A solid understanding of key BI trends.


  • Advanced degree in Applied Mathematics, Business Analytics, Statistics, Machine Learning, Computer Science or related fields is a plus.